Statsmodels Statistical Analysis

About

Statsmodels is an advanced Python library for statistical modeling, providing comprehensive tools for estimation, inference, and diagnostics. This skill enables Claude to perform everything from simple linear regressions and generalized linear models (GLM) to complex time-series forecasting (ARIMA) and econometric analyses. It is essential for data scientists and researchers who require production-ready statistical tables, rigorous hypothesis testing, and deep diagnostic validation of model assumptions like heteroskedasticity and autocorrelation.

Key Features

• Comprehensive time series analysis including ARIMA, SARIMAX, and VAR
• R-style formula API for intuitive model specification
• Advanced diagnostic tests for normality, heteroskedasticity, and autocorrelation
• Linear and Generalized Linear Models (OLS, GLM, Logistic, Poisson)
• 0 GitHub stars
• Production-ready statistical summaries and inference tables

Use Cases

• Building and validating econometric models for financial or social data
• Performing hypothesis testing and causal effect estimation for scientific research
• Forecasting future trends using seasonal and non-seasonal time series data